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No-Reference Fingerprint Image Quality Assessment

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Intelligent Computing Methodologies (ICIC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8589))

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Abstract

Quality of a fingerprint image is assessed to control the registration of poor quality images in the database so that a good accuracy of fingerprint recognition system can be achieved. This paper proposes a quality assessment scheme for digital fingerprint image. It makes use of complete ridge line of a thinned fingerprint image for quality assessment. It introduces three robust measures (1) ridge-line smoothness (2) inter ridge-line distance and (3) minutiae extractability for the quality assessment. Experiments are performed on a database comprising of 1000 fingerprint images of 500 subjects of various age group lying between 18 and 75. It has been found that the performance of the fingerprint recognition system is improved from CRR of 74.6% to 100% and EER of 13.08% to 0.01% by controlling the registration of inferior quality fingerprint in the database. Quality of a fingerprint images is an important indicator of its performance in automatic fingerprint based recognition system.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, 208016, India

    Kamlesh Tiwari & Phalguni Gupta

Authors
  1. Kamlesh Tiwari
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  2. Phalguni Gupta
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Electrical Engineering, University of Ulsan, 680–749, Ulsan, Korea

    Kang-Hyun Jo

  3. Department of Automation, Tsinghua University, Bejing, China

    Ling Wang

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Tiwari, K., Gupta, P. (2014). No-Reference Fingerprint Image Quality Assessment. In: Huang, DS., Jo, KH., Wang, L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer Science(), vol 8589. Springer, Cham. https://doi.org/10.1007/978-3-319-09339-0_85

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  • DOI: https://doi.org/10.1007/978-3-319-09339-0_85

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09338-3

  • Online ISBN: 978-3-319-09339-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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